Method of trading in real estate derivatives

ABSTRACT

A method of computing a real estate derivative index value includes: selecting asking rent data; selecting lease rent data; and combining the selected asking rent data and the selected lease rent data to form the index value. The method may further include further combining the combined data with a value representative of general market conditions; forming a composite index of data from plural markets; or computing the index at the end of a time period as: 
       Δ FKI or as Δ RP+Δ CPI+Δ FKI. 
     The method may further include trading based on the index by deriving a trade value from the index value, and executing a trade based on the derived trade value. The method may be carried as instructions on a machine-readable medium and may be carried out using a computer for part or all of the method.

RELATED APPLICATION

The present application is a non-provisional application claiming thebenefit under 35 U.S.C. § 119(e) of U.S. Provisional application Ser.No. 60/887,451, filed on Jan. 31, 2007, the contents of which are herebyincorporated by reference.

DETAILED DESCRIPTION

This invention is not limited in its application to the details ofconstruction and the arrangement of components set forth in thefollowing description or illustrated in the drawings. The invention iscapable of other embodiments and of being practiced or of being carriedout in various ways. Also, the phraseology and terminology used hereinis for the purpose of description and should not be regarded aslimiting. The use of “including,” “comprising,” or “having,”“containing”, “involving”, and variations thereof herein, is meant toencompass the items listed thereafter and equivalents thereof as well asadditional items.

According to an exemplary embodiment of aspects of the inventionreferred to as the Rexx Real Estate Property Index, the Rexx Indexcalculates Total Return in commercial real estate for the US marketbased on lease transaction prices, asking rents, Effective Fed Funds,and CPI. The approach is to identify the change in valuation ofcommercial real estate from current macro and micro economic marketconditions as they occur, in contrast to indeterminate average meansales pairs or lagging appraisals and net income. When Rexx Indexreturns are benchmarked against indices prepared by Real EstateInvestment Fiduciaries and transactional indices from independentresearch firms, both of which are lagging indicators, the Rexx Indexprovides a highly-correlated, leading reference point to current marketconditions and change in valuation of commercial real estate inindividual and broad markets. These results are a function of the dataand the A Rent Model used in the construction of the Rexx Index which isstatistically significant and can be used in all market conditions forall periods in question.

The Rexx Real Estate Property Index is based on a Δ Rent Model asexplained below, and calculates Total Return, Capital Return and Δ RentReturn for 15 individual markets Atlanta, Boston, Chicago, Dallas,Denver, Houston, LA, NY Midtown, NY Midtown South, NY Downtown, Phoenix,San Francisco, Seattle, Miami, DC, and the broad market Rexx CompositeIndex. Of course, the selection of individual and composite marketcompositions is arbitrary and within the skill of the artisan in thisfield.

The Rexx Total Return, Rexx Capital Return, and Rexx A Rent Return forIndividual Markets and the Rexx Composite Index can be published on anyconvenient schedule, for example, quarterly in February, May, August andNovember.

If published according to the exemplary schedule, for example, then datacollected for the period April, May, and June is published in August,for the quarter period ending June 30th.

The Δ Rent Model stands on data which is transparent and statisticallysignificant and can be used in all market conditions for all periods inquestion. The benefit of the Δ Rent Model is apparent when compared tomethods which are moderately successful in the valuation process on a“look back” basis, and are universally accepted to have extremedifficulty in the measurement of current market performance.

The Δ Rent Model uses the most fundamental and transparent informationwhich landlords and tenants evaluate supply and demand in the commercialreal estate market coupled with the impact of risk premium and costadjustment to determine total return for the period in question. The ΔRent Model does not rely on coefficients to offset unknown conditionsand free radicals, rolling averages for lack of data, or manipulation ofthe data set over time. The Δ Rent Model does not rely on NOI, Cap Rate,and Stock Weighting which have proven ineffective in current marketvaluation.

The Δ Rent model determines total return in the commercial real estatemarket for all periods in questions based on the following assumptions:

-   1) Assets that produce risk free rates of return do not increase in    value. Assets that produce returns above the risk free rate of    return increase in value. Assets that produce returns below the risk    free rate of return decrease in value.-   2) Real estate assets provide on-going return based on inflation    tied to CPI and other rent escalation clauses.-   3) Real estate revenue is dependent upon rent.

All data used in the calculation of the Rexx Index is available to thegeneral public, either from public or private sources, some of which mayrequire licenses from their owners. Real estate lease transaction andasking rent data is selected on the basis of specific filters, qualitycontrol, and market coverage provided by the leading global real estatebrokerage and research firms. Interest rate data is compiled from the USFederal Reserve, and Inflation data is compiled from the US Bureau ofLabor Statistics.

The Δ Rent Model for all periods in question is based on the equation:

Total Market Return=Δ RP+Δ CPI+Δ FKI

Δ RP=Risk Premium (∞ Equilibrium−Δ FFR)

∞ Equilibrium=Average Total Return of Commercial real estate inequilibrium (end-point equilibrium)

Δ FFR=Effective Fed Funds Rate

Δ CPI=Urban Consumer CPI Inflation rate year over year.Δ FKI=value change based on asking rent and lease transaction pricing ofan individual market.∞ Equilibrium is critical to understanding the Δ Rent Model. ∞Equilibrium is the point when average total return is no longer changingand fixed, for all total return accumulated to ∞/∞, since at this pointthere are no additional returns to be considered.

In estimating ∞ Equilibrium, long term average total return incommercial real estate has consistently ranged between 8-12%. In the ΔRent Model, ∞ Equilibrium has been set =10.

The functionality and transparency of the Δ Rent model is the ability tomeasure the impact of macro economic factors in commercial real estateindependent from individual market supply and demand conditions.

Rexx Capital Return=ΔRP+Δ CPI

Δ RP=value change from risk premium (∞ Equilibrium−Δ FFR)Δ CPI=value change from inflationWith increases and decreases in the risk premium as measured by Δ RP,the value of commercial real estate increases and decreases in directrelationship for the period in question. With increases and decreases inthe rate of inflation as measured by Δ CPI, the value of commercial realestate increases and decreases in direct relationship for the period inquestion.

Individual market performance is subject to micro economic conditionsmeasured in the Δ Rent Model through asking rent and lease transactionpricing. The abundance of information related to these conditions iswell documented, and the Δ Rent Model uses data of sufficient marketcoverage, reliability, and consistent application to determine currentmarket return which includes unforeseen events and natural markettrends.

Individual Market Δ FKI is calculated as follows:

Δ FKI=(R1−R0)/(R0)*100

Δ FKI=value change in commercial real estate from individual marketconditions.R1=ending asking rent and lease transaction pricing for the individualmarket for the period in question.R0=beginning asking rent and lease transaction pricing for theindividual market for the period in question.

Rexx Index (IM) Total Return is calculated from the following equationfor all individual markets, for all time periods in question, in allmarket conditions.

Rexx (IM) Total Return=Rexx Capital+Rexx (IM) Δ Rent Rexx Capital=Δ RP+ΔCPI Rexx (IM) ERent=Δ FKI

For example, for Market Index period: 4 qtr 2005:

Rexx Chicago Total Return=Δ RP+Δ CPI+Chicago Δ FKI=2.965

Rexx Capital=2.435 Δ RP=1.505+Δ CPI=0.93 Chicago Δ FKI=0.53

Rexx Dallas Total Return=Δ RP+Δ CPI+Dallas Δ FKI=4.705

Rexx Capital=2.435 Δ RP=1.505+Δ CPI=0.93 Dallas Δ FKI=2.27

The Rexx Index Office Composite includes individual markets with aminimum of 25,000,000 sq ft of Class A office space, a minimum of 100Class A office buildings, and sufficient research and advisory servicesto provide reliable reporting of market conditions for the period inquestion. Other criteria for selecting the individual markets formingthe composite may be used. The individual market and composite indexselection process does not limit the use of the Δ Rent Model. Otherindividual market indices and other composite indices corresponding to adifferent mix of markets or additional markets may be calculated asrequired.

Markets that can be calculated, under the above criteria, include, butare not limited to: Atlanta, Boston, Chicago, Dallas, Denver, Houston,LA, NY Midtown, NY Midtown South, NY Downtown, Phoenix, San Francisco,Seattle, Miami, DC.

All Rexx Composite Indices are equal weighted by individual market. Thebenefit of the Rexx Composite Index weighting allows for individualmarket comparison to the overall US Market performance, and the abilityto measure performance based on individual portfolio holdings permarket.

The Rexx Δ Rent calculation provides the measure for the supply anddemand of all individual markets in the Rexx Δ Rent Composite. Whichmarkets are included in each calculation can be varied, as desired bythe index manager. The Rexx Δ Rent Calculation provides the measurementof supply and demand for all individual markets, without macro economicfactors, and provides the basis to determine whether an individualmarket has performed above or below the average benchmark in the USmarket, and the basis for individual market to market comparison.

Rexx Composite Total Return=all individual market Total Returns/numberof markets included

In the exemplary embodiment, the number of markets included=15.

Trades based on the Rexx index, its components and its composites can beexecuted using any suitable mechanism. For example, options, futures,swaps and derivatives may all be traded in any suitable market on anysuitable exchange. Prediction markets and exchanges, and spread-bettingmarkets and exchanges, are two suitable market/exchange arrangements.These types of trades, markets and exchanges are briefly defined below.

Definitions of Trade Types

Term Definition option The right, but not the obligation, to buy (for acall option) or sell (for a put option) a specific amount of a givenstock, commodity, currency, index, or debt, at a specified price (thestrike price) during a specified period of time. For stock options, theamount is usually 100 shares. Each option has a buyer, called theholder, and a seller, known as the writer. If the option contract isexercised, the writer is responsible for fulfilling the terms of thecontract by delivering the shares to the appropriate party. In the caseof a security that cannot be delivered such as an index, the contract issettled in cash. For the holder, the potential loss is limited to theprice paid to acquire the option. When an option is not exercised, itexpires. No shares change hands and the money spent to purchase theoption is lost. For the buyer, the upside is unlimited. Options, likestocks, are therefore said to have an asymmetrical payoff pattern. Forthe writer, the potential loss is unlimited unless the contract iscovered, meaning that the writer already owns the security underlyingthe option. Options are most frequently as either leverage orprotection. As leverage, options allow the holder to control equity in alimited capacity for a fraction of what the shares would cost. Thedifference can be invested elsewhere until the option is exercised. Asprotection, options can guard against price fluctuations in the nearterm because they provide the right acquire the underlying stock at afixed price for a limited time. risk is limited to the option premium(except when writing options for a security that is not already owned).However, the costs of trading options (including both commissions andthe bid/ask spread) is higher on a percentage basis than trading theunderlying stock. In addition, options are very complex and require agreat deal of observation and maintenance. This type of trade is alsocalled option contract. futures A standardized, transferable,exchange-traded contract that requires delivery of a commodity, bond,currency, or stock index, at a specified price, on a specified futuredate. Unlike options, futures convey an obligation to buy. The risk tothe holder is unlimited, and because the payoff pattern is symmetrical,the risk to the seller is unlimited as well. Dollars lost and gained byeach party on a futures contract are equal and opposite. In other words,futures trading is a zero-sum game. Futures contracts are forwardcontracts, meaning they represent a pledge to make a certain transactionat a future date. The exchange of assets occurs on the date specified inthe contract. Futures are distinguished from generic forward contractsin that they contain standardized terms, trade on a formal exchange, areregulated by overseeing agencies, and are guaranteed by clearinghouses.Also, in order to insure that payment will occur, futures have a marginrequirement that must be settled daily. Finally, by making an offsettingtrade, taking delivery of goods, or arranging for an exchange of goods,futures contracts can be closed. Hedgers often trade futures for thepurpose of keeping price risk in check. This type of trade is alsocalled futures contract. swap An exchange of streams of payments overtime according to specified terms. The most common type is an interestrate swap, in which one party agrees to pay a fixed interest rate inreturn for receiving an adjustable rate from another party. derivative Afinancial instrument whose characteristics and value depend upon thecharacteristics and value of an underlier, typically a commodity, bond,equity or currency. Examples of derivatives include futures and options.Advanced investors sometimes purchase or sell derivatives to manage therisk associated with the underlying security, to protect againstfluctuations in value, or to profit from periods of inactivity ordecline. These techniques can be quite complicated and quite risky.

Definitions of Market and Exchange Types

Term Definition field A field is a structured space of power andresources with its own forms of competition and reward. Markets are animportant part of fields, but fields are much more than markets: Theyare also made up of agents and organizations and the relations amongthem, of networks and supply chains, of different kinds and quantitiesof power and resources that are distributed in certain ways, of specificpractices and forms of competition, and so on. Each field has adistinctive dynamic that has evolved over time. The logic of the fielddefines the conditions under which agents and organizations canparticipate in the field and flourish or falter within it - that is, theconditions under which they can play the game. market A market isdefined as a place where buyers and sellers get together and set pricesand quantities. exchange An exchange is an organized market withtransactions concentrated in a physical facility with participantsentering two-sided quotations (bid and ask) on a continuous basis.prediction An exchange that organizes prediction markets. exchangeSynonyms: event-driven futures exchange - (U.S.A.); event futuresexchange - (U.S.A.); betting exchange - (U.K., Ireland, Australia);person-to-person betting exchange; peer-to-peer betting exchange; P2Pbetting exchange. Originally, prediction exchanges use real money.However, some play-money prediction exchanges have shown some form ofaccuracy. betting (U.K.) Betting exchanges exist to match people whowant to bet on a exchange future outcome at a given price with otherswho are willing to offer that price. The person who bets on the eventhappening at a given price is the backer. The person who offers theprice is known as the layer, and is essentially acting in the same wayas a bookmaker. The advantage of this form of betting for the bettor isthat, by allowing anyone with access to a betting exchange to offer orlay odds, it serves to reduce margins in the odds compared to the bestodds on offer with traditional bookmakers. Exchanges allow clients toact as a bettor (backer) or bookmaker (layer) at will, and indeed toback and lay the same event at different times during the course of themarket. The way in which this operates is that the major bettingexchanges present clients with the three best odds and stakes whichother members of the exchange are offering or asking for. For example,for England to beat Brazil at football the best odds on offer might be 4to 1, to a maximum stake of £80, 3.5 to 1 to a further stake of £100 and3 to 1 to a further stake of £500. This means that potential backers canstake up to a maximum of £80 on England to beat Brazil at odds of 4 to1, a further £100 at 3.5 to 1 and a further £500 at 3 to 1. These odds,and the staking levels available, may have been offered by one or moreother clients who believe that the true odds were longer than theyoffered. An alternative option available to potential backers is toenter the odds at which they would be willing to place a bet, togetherwith the stake they are willing to wager at that odds level. Thisrequest (say £50 at 4 to 1) will then be shown on the request side ofthe exchange, and may be accommodated by a layer at any time until theevent is over. The margin between the best odds on offer and the bestodds sought tends to narrow as more clients offer and lay bets, so thatin popular markets the real margin against the bettor (or layer) tendstowards the commission levied (normally on winning bets) by theexchange. This commission varies from about 2 per cent to 5 per cent.spread- An exchange that matches spread bettors. betting The nature ofspread betting is that the more punters are right, the exchange morethey win, and vice versa. A spread bet asks punters to estimate whethera pre-determined outcome will be above or below a given range. Thepotential gain or loss depends on how far above or below that range thenumber will be. prediction Prediction markets are designed specificallyto forecast events. - markets Some are markets designed specifically forinformation aggregation and revelation. Prediction markets are usuallydesigned and conducted for the purpose of aggregating information sothat market prices forecast future events. These markets differ fromtypical, naturally occurring markets in their primary role as aforecasting tool instead of a resource allocation mechanism.Participants trade in contracts whose payoff depends on unknown futureevents. Prediction markets - also called idea futures markets orinformation markets - are designed to aggregate information and producepredictions about future events: for example, a political candidate'sre-election, or a box-office take, or the probability that the FederalReserve will increase interest rates at its next meeting. To elicit suchpredictions, contract payoffs are tied to unknown future events. Forexample, a contract might pay $100 if George Bush is re-elected in 2004,or nothing if he is not. Thus, until the outcome is decided, the tradingprice reflects the traders' collective consensus about the expectedvalue of the contract, which in this case is exactly proportional to theprobability of Bush's re-election. Information Prediction marketsspecifically created to aggregate information. markets Such marketsusually estimate a probability distribution over the values of certainvariables, via bets on those values. A market designed from the outsetfor information gathering and forecasting is called an informationmarket. Information markets can be used to elicit a collective estimateof the expected value or probability of a random variable, reflectinginformation dispersed across an entire population of traders. The marketprediction is not usually an average or median of individual opinions,but is a complex summarization reflecting the game-theoretic interplayof traders as they obtain and leverage information, and as they react tothe actions of others obtaining and leveraging their own information,etc. In the best case scenario, the market price reflects a forecastthat is a perfect Bayesian integration of all the information spreadacross all of the traders, properly accounting even for redundancy. Thisis the equilibrium scenario called rational expectations in theeconomics literature, and is the assumption underlying the strong formof the efficient markets hypothesis in finance.

Several different suitable market structures can be used, includingconventional continuous double auction markets, combinatorialinformation markets and double pari-mutuel markets.

Combinatorial information markets use market scoring rules ascombinatorial information market makers.

Information markets are markets created to aggregate information. Suchmarkets usually estimate a probability distribution over the values ofcertain variables, via bets on those values. Combinatorial informationmarkets would aggregate information on the entire joint probabilitydistribution over many variables, by allowing bets on all variable valuecombinations. To achieve this, we want to overcome the thin market andirrational participation problems that plague standard informationmarkets. Scoring rules avoid these problems, but instead suffer fromopinion pooling problems in the thick market case. Market scoring rulesavoid all these problems, by becoming automated market makers in thethick market case and simple scoring rules in the thin market case.Logarithmic versions have cost and modularity advantages.

While a simple information market lets one trade on the probability ofeach value of a single variable, a combinatorial information market letsone trade on any combination of a set of variables, including anyconditional or joint probability.

A dynamic pari-mutuel market (DPM) acts as hybrid between a pari-mutuelmarket and a continuous double auction (CDA), inheriting some of theadvantages of both. A DPM offers infinite buy-in liquidity and zero riskfor the market institution; like a CDA, a DPM can continuously react tonew information, dynamically incorporate information into prices, andallow traders to lock in gains or limit losses by selling prior to eventresolution. The trader interface can be designed to mimic the familiardouble auction format with bid-ask queues, though with an additionvariable called the payoff per share. The DPM price function can beviewed as an automated market maker always offering to sell at someprice, and moving the price appropriately according to demand. Since themechanism is pari-mutuel (i.e., redistributive), it is guaranteed to payout exactly the amount of money taken in.

All the necessary computations to implement the index, its derivatives,trades, and markets and exchanges can be carried out by computer.Embodiments using computers may incorporate systems as now described.

Various aspects of some embodiments according to the invention may beimplemented on one or more computer systems. These computer systems maybe, for example, general-purpose computers such as those based on IntelPENTIUM-type processor, Motorola PowerPC, Sun UltraSPARC,Hewlett-Packard PA-RISC processors, or any other type of processor. Itshould be appreciated that one or more of any type computer system maybe used to perform various trading-related tasks according to variousembodiments of the invention. Further, one or more portions of a realestate derivatives trading system may be located on a single computer ormay be distributed among a plurality of computers attached by acommunications network.

A general-purpose computer system according to one embodiment of theinvention is configured to perform any of the described functionsrelated to trading real estate derivatives including but not limited tocomputing values of an index to be traded or components thereof,evaluating a portfolio and changes thereto and communicating tradeinformation between investors and traders. It should be appreciated thatthe system may perform other functions, including network communication,and the invention is not limited to having any particular function orset of functions.

For example, various aspects of the invention may be implemented asspecialized software executing in a general-purpose computer system 100such as that shown in FIG. 1. The computer system 100 may include aprocessor 103 connected to one or more memory devices 104, such as adisk drive, memory, or other device for storing data. Memory 104 istypically used for storing programs and data during operation of thecomputer system 100. Components of computer system 100 may be coupled byan interconnection mechanism 105, which may include one or more busses(e.g., between components that are integrated within a same machine)and/or a network (e.g., between components that reside on separatediscrete machines). The interconnection mechanism 105 enablescommunications (e.g., data, instructions) to be exchanged between systemcomponents of system 100.

Computer system 100 also includes one or more input devices 102, forexample, a keyboard, mouse, trackball, microphone, touch screen, and oneor more output devices 101, for example, a printing device, displayscreen, speaker. In addition, computer system 100 may contain one ormore interfaces (not shown) that connect computer system 100 to acommunication network (in addition or as an alternative to theinterconnection mechanism 105.

The storage system 106, shown in greater detail in FIG. 2, typicallyincludes a computer readable and writeable nonvolatile recording medium201 in which signals are stored that define a program to be executed bythe processor or information stored on or in the medium 201 to beprocessed by the program. The medium may, for example, be a disk orflash memory. Typically, in operation, the processor causes data to beread from the nonvolatile recording medium 201 into another memory 202that allows for faster access to the information by the processor thandoes the medium 201. This memory 202 is typically a volatile, randomaccess memory such as a dynamic random access memory (DRAM) or staticmemory (SRAM). It may be located in storage system 106, as shown, or inmemory system 104, not shown. The processor 103 generally manipulatesthe data within the integrated circuit memory 104, 202 and then copiesthe data to the medium 201 after processing is completed. A variety ofmechanisms are known for managing data movement between the medium 201and the integrated circuit memory element 104, 202, and the invention isnot limited thereto. The invention is not limited to a particular memorysystem 104 or storage system 106.

The computer system may include specially-programmed, special-purposehardware, for example, an application-specific integrated circuit(ASIC). Aspects of the invention may be implemented in software,hardware or firmware, or any combination thereof. Further, such methods,acts, systems, system elements and components thereof may be implementedas part of the computer system described above or as an independentcomponent.

Although computer system 100 is shown by way of example as one type ofcomputer system upon which various aspects of the invention may bepracticed, it should be appreciated that aspects of the invention arenot limited to being implemented on the computer system as shown inFIG. 1. Various aspects of the invention may be practiced on one or morecomputers having a different architecture or components that that shownin FIG. 1.

Computer system 100 may be a general-purpose computer system that isprogrammable using a high-level computer programming language. Computersystem 100 may be also implemented using specially programmed, specialpurpose hardware. In computer system 100, processor 103 is typically acommercially available processor such as the well-known Pentium classprocessor available from the Intel Corporation. Many other processorsare available. Such a processor usually executes an operating systemwhich may be, for example, the Windows 95, Windows 98, Windows NT,Windows 2000 (Windows ME) or Windows XP operating systems available fromthe Microsoft Corporation, MAC OS System X operating system availablefrom Apple Computer, the Solaris operating system available from SunMicrosystems, or UNIX operating systems available from various sources.Many other operating systems may be used.

The processor and operating system together define a computer platformfor which application programs in high-level programming languages arewritten. It should be understood that the invention is not limited to aparticular computer system platform, processor, operating system, ornetwork. Also, it should be apparent to those skilled in the art thatthe present invention is not limited to a specific programming languageor computer system. Further, it should be appreciated that otherappropriate programming languages and other appropriate computer systemscould also be used.

One or more portions of the computer system may be distributed acrossone or more computer systems coupled to a communications network. Thesecomputer systems also may be general-purpose computer systems. Forexample, various aspects of the invention may be distributed among oneor more computer systems configured to provide a service (e.g., servers)to one or more client computers, or to perform an overall task as partof a distributed system. For example, various aspects of the inventionmay be performed on a client-server or multi-tier system that includescomponents distributed among one or more server systems that performvarious functions according to various embodiments of the invention.These components may be executable, intermediate (e.g., IL) orinterpreted (e.g., Java) code which communicate over a communicationnetwork (e.g., the Internet) using a communication protocol (e.g.,TCP/IP).

It should be appreciated that the invention is not limited to executingon any particular system or group of systems. Also, it should beappreciated that the invention is not limited to any particulardistributed architecture, network, or communication protocol.

Various embodiments of the present invention may be programmed using anobject-oriented programming language, such as SmallTalk, Java, C++, Ada,or C# (C-Sharp). Other object-oriented programming languages may also beused. Alternatively, functional, scripting, and/or logical programminglanguages may be used. Various aspects of the invention may beimplemented in a non-programmed environment (e.g., documents created inHTML, XML or other format that, when viewed in a window of a browserprogram, render aspects of a graphical-user interface (GUI) or performother functions). Various aspects of the invention may be implemented asprogrammed or non-programmed elements, or any combination thereof.

Having thus described several aspects of at least one embodiment of thisinvention, it is to be appreciated various alterations, modifications,and improvements will readily occur to those skilled in the art. Suchalterations, modifications, and improvements are intended to be part ofthis disclosure, and are intended to be within the spirit and scope ofthe invention. Accordingly, the foregoing description and drawings areby way of example only.

1. A method for matching buy and sell orders, comprising the steps of:maintaining a daily cash index of real estate values for a local regionbased on real estate transactional activity and real estatetransactions; creating a trading instrument representative of aninterest in real estate in the local region, wherein a cash settlementof the trading instrument is a function of the daily cash index on thedate of said cash settlement; generating a plurality of buy ordersrelating to the instrument; generating a plurality of sell ordersrelating to the instrument; and matching the buy and sell orders todetermine a purchase and sale of the instrument.
 2. The method of claim1, wherein the trading instrument is a futures contract.
 3. The methodof claim 1, wherein the trading instrument is a forward contract.
 4. Themethod of claim 1, wherein the trading instrument is an option on afutures contract.
 5. The method of claim 1, wherein the tradinginstrument is an option on a forward contract.
 6. The method of claim 1,wherein each day's daily cash index is generated as a function of asurvey of actual real estate transactions executed on said day.
 7. Themethod of claim 6, wherein the real estate transactions are real estateleases.
 8. The method of claim 6, wherein the daily cash index iscalculated on a weighted average basis.
 9. The method of claim 6,wherein the daily cash index is calculated on a moving average basis.10. The method of claim 6, wherein the daily cash index is calculated onan exponential moving average basis.
 11. The method of claim 8, whereinthe daily cash index is weighted according to building classes, whereinthe building classes include at least Class A building, Class Bbuildings, and Class C buildings.
 12. The method of claim 1, wherein thedaily cash index is aggregated on a monthly basis to provide a monthlyindex value.
 13. The method of claim 1, further comprising generating avolatility value of the daily cash index, said volatility value being afunction of a historic performance of the daily cash index.
 14. Themethod of claim 13, wherein the historic performance is a function ofaggregated monthly values of the daily cash index over a plurality ofyears.
 15. A method for trading futures contracts in real estate,comprising the steps of: a. maintaining a daily cash index of realestate values for a local region based upon real estate transactionalactivity and real estate transactions; b. creating a futures contractrepresentative of an interest in real estate in the local region, thefutures contract having a settlement date, wherein a cash settlement ofthe futures contract is a function of the daily cash index on thesettlement date; c. receiving a plurality of buy orders relating to thefutures contract; d. receiving a plurality of sell orders relating tothe futures contract; e. matching the buy and sell orders to determine apurchase and sale of the futures contract.
 16. The method of claim 15,wherein the daily cash index is aggregated on a monthly basis to providea monthly index value.
 17. A method for providing indices for commercialreal estate lease values, comprising: a. each day, performing a surveyof actual commercial real estate leases executed on said day andcommercial real estate lease transactional activity for said day in alocal region; b. each day, generating a daily cash index of commercialreal estate lease values in the local region based upon the survey; c.each month, aggregating the daily surveys on a monthly basis to generatea monthly cash index; d. generating a volatility value based upon themonthly cash indices over a plurality of years.
 18. The method of claim17, wherein the daily cash index is calculated on a weighted averagebasis.
 19. The method of claim 17, wherein the daily cash index iscalculated on a moving average basis.
 20. The method of claim 16,wherein the daily cash index is calculated on an exponential movingaverage basis.
 21. The method of claim 18, wherein the daily cash indexis weighted according to building classes, wherein the building classesinclude at least Class A building, Class B buildings, and Class Cbuildings.
 22. A method for providing indices for real estatetransaction values, comprising: a. each day, performing a survey ofactual real estate transactions executed on said day, and real estatetransactional activity for said day, in a local region; b. each day,generating a daily cash index of real estate transaction values in thelocal region based upon the survey.
 23. A method for matching buy andsell orders, comprising the steps of: maintaining a daily cash index ofreal estate values for a local region based on real estate transactionalactivity; creating a trading instrument representative of an interest inreal estate in the local region, wherein a cash settlement of thetrading instrument is a function of the daily cash index on the date ofsaid cash settlement; generating a plurality of buy orders relating tothe instrument; generating a plurality of sell orders relating to theinstrument; and matching the buy and sell orders to determine a purchaseand sale of the instrument.
 24. The method of claim 22, wherein thedaily cash index is calculated on a weighted average basis.
 25. Themethod of claim 22, wherein the daily cash index is calculated on amoving average basis.
 26. The method of claim 22, wherein the daily cashindex is calculated on an exponential moving average basis.
 27. Themethod of claim 24, wherein the daily cash index is weighted accordingto building classes, wherein the building classes include at least ClassA building, Class B buildings, and Class C buildings.
 28. The method ofclaim 22, wherein the real estate transactions and real estatetransactional activity are for commercial real estate leases.
 29. Themethod of claim 22, wherein the real estate transactions and real estatetransactional activity are for residential real estate leases.
 30. Themethod of claim 22, wherein the real estate transactions and real estatetransactional activity are for rural land real estate leases.
 31. Themethod of claim 22, wherein the real estate transactions and real estatetransactional activity are for industrial real estate leases.
 32. Amethod for providing indices for real estate transaction values,comprising: a. based upon historical data, generating monthly cashindices of real estate values in a local region for each month of atleast 10 prior years; b. generating a an initial volatility value basedupon the monthly cash indices over said at least 10 prior years; c. eachday, performing a survey of actual real estate transactions executed onsaid day, and real estate transactional activity for said day, in thelocal region; d. each day, generating a daily cash index of real estatetransaction values in the local region based upon the survey; e. eachmonth, aggregating the daily surveys on a monthly basis to generate amonthly cash index for said each month; and f. updating the volatilityvalue based upon each monthly cash index generated in step
 33. A methodfor providing indices for commercial real estate lease values,comprising: a. based upon historical data, generating monthly cashindices of commercial real estate values in a local region for eachmonth of at least 10 prior years; b. generating a an initial volatilityvalue based upon the monthly cash indices over said at least 10 prioryears; c. each day, performing a survey of actual commercial real estateleases executed on said day and commercial real estate transactions forsaid day in the local region; d. each day, generating a daily cash indexof commercial real estate lease values in the local region based uponthe survey; e. each month, aggregating the daily surveys on a monthlybasis to generate a monthly cash index for said each month; and f.updating the volatility value based upon each monthly cash indexgenerated in step.
 34. The method of claim 33, wherein the daily cashindex is calculated on a weighted average basis.
 35. The method of claim33, wherein the daily cash index is calculated on a moving averagebasis.
 36. The method of claim 33, wherein the daily cash index iscalculated on an exponential moving average basis.
 37. The method ofclaim 34, wherein the daily cash index is weighted according to buildingclasses, wherein the building classes include at least Class A building,Class B buildings, and Class C buildings.
 38. A method of operating anexchange, comprising: a. at a daily cash market source, i. each day,performing a survey of actual commercial real estate transactionsexecuted on said day and commercial real estate transactional activityfor said day in a local region; ii. each day, generating a daily cashindex of commercial real estate transaction values in the local regionbased upon the survey; b. at an exchange, creating a trading instrumentrepresentative of an interest in real estate in the local region,wherein a cash settlement of the trading instrument is a function of thedaily cash index on the date of said cash settlement; c. at each of aplurality of exchange members, generating a plurality of buy orders anda plurality of sell orders for the trading instrument; and d. at theexchange, i. matching the buy and sell orders to determine a purchaseand sale of the instrument, each purchase having a purchase price paidby its corresponding buy order and each sale having a sale price paid toits corresponding sell order; ii. sending a portion of each purchaseprice to each of a plurality of investors in the exchange.
 39. A methodfor providing indices for commercial real estate transaction values,comprising: a. each day, performing a survey of commercial real estatetransactional activity on said day in a local region; b. each day,generating a daily cash index of commercial real estate transactionvalues in the local region based upon the survey; c. each month,aggregating the daily surveys on a monthly basis to generate a monthlycash index; d. generating a volatility value based upon the monthly cashindices over a plurality of years.
 40. A method of operating anexchange, comprising: a. at a daily cash market source, i. each day,performing a survey of actual commercial real estate leases executed onsaid day, and/or commercial real estate transactional activity for saidday, in a local region; ii. each day, generating a daily cash index ofcommercial real estate lease values in the local region based upon thesurvey; b. at an exchange, creating a trading instrument representativeof an interest in real estate in the local region, wherein a cashsettlement of the trading instrument is a function of the daily cashindex on the date of said cash settlement; c. at each of a plurality ofexchange members, generating a plurality of buy orders and a pluralityof sell orders for the trading instrument; and d. at the exchange, i.matching the buy and sell orders to determine a purchase and sale of theinstrument, each purchase having a purchase price paid by itscorresponding ii. buy order and each sale having a sale price paid toits corresponding sell order; iii. sending a portion of each purchaseprice to each of a plurality of investors in the exchange.
 41. Themethod of claim 23, wherein the daily cash index is also based on realestate transactions.
 42. A method for matching buy and sell orders,comprising the steps of: maintaining a daily cash index of real estatevalues for a local region based on real estate transactional activity;creating a trading instrument representative of an interest in realestate in the local region, wherein a cash settlement of the tradinginstrument is a function of the daily cash index on the date of saidcash settlement; generating a plurality of buy orders relating to theinstrument; generating a plurality of sell orders relating to theinstrument; and matching the buy and sell orders to determine a purchaseand sale of the instrument
 43. A method for matching buy and sellorders, comprising the steps of: maintaining a daily cash index of realestate values for a local region based on real estate statistics;creating a trading instrument representative of an interest in realestate in the local region, wherein a cash settlement of the tradinginstrument is a function of the daily cash index on the date of saidcash settlement; generating a plurality of buy orders relating to theinstrument; generating a plurality of sell orders relating to theinstrument; and matching the buy and sell orders to determine a purchaseand sale of the instrument.
 44. A computer-implemented method of tradingin real estate derivatives, the method comprising: selecting data fromat least one of asking rent data and lease rent data; and combining theselected data to form the index value; deriving a trade value from theindex value; and executing a trade based on the derived trade value. 45.The computer-implemented method of claim 44, wherein selecting datafurther comprises: selecting data from both asking rent data and leaserent data.
 46. The computer-implemented method of claim 44, wherein theindex is computed at the end of a time period as:Δ FKI.
 47. The computer-implemented method of claim 44, furthercomprising: further combining the combined data with a valuerepresentative of general market conditions.
 48. Thecomputer-implemented method of claim 47, wherein the index is acomposite formed of data from plural markets.
 49. Thecomputer-implemented method of claim 47, wherein the index is computedat the end of a time period as:Δ RP+Δ CPI+ΔFKI.
 50. A method of computing a real estate derivativeindex value, the method comprising: selecting data from at least one ofasking rent data and lease rent data; and combining the selected data toform the index value.
 51. The method of claim 50, wherein selecting datafurther comprises: selecting data from both asking rent data and leaserent data.
 52. The method of claim 50, wherein the index is computed atthe end of a time period as:Δ FKI.
 53. The method of claim 50, further comprising: further combiningthe combined data with a value representative of general marketconditions.
 54. The method of claim 53, wherein the index is a compositeformed of data from plural markets.
 55. The method of claim 53, whereinthe index is computed at the end of a time period as:Δ RP+Δ CPI+Δ FKI.
 56. A machine-readable medium carrying instructionsfor carrying out in a computer: selecting data from at least one ofasking rent data and lease rent data; and combining the selected data toform an index value.
 57. The machine-readable medium of claim 56,further carrying instructions for carrying out in a computer: selectingdata from both asking rent data and lease rent data.
 58. Themachine-readable medium of claim 56, further carrying instructions forcarrying out in a computer: computing an index at the end of a timeperiod as:Δ FKI.
 59. The method of claim 56, further comprising: further combiningthe combined data with a value representative of general marketconditions.
 60. The machine-readable medium of claim 59, furthercarrying instructions for carrying out in a computer: forming the indexas a composite of data from plural markets.
 61. The machine-readablemedium of claim 59, further carrying instructions for carrying out in acomputer: computing the index value at the end of a time period as:Δ RP+Δ CPI+Δ FKI.